1 들어오고
2 나가고
block Tensor("input_3:0", shape=(?, 256, 256, 3), dtype=float32) 256 3 False 3 64
block Tensor("leaky_re_lu_5/sub:0", shape=(?, 128, 128, 64), dtype=float32) 128 64 True None None
block Tensor("leaky_re_lu_6/sub:0", shape=(?, 64, 64, 128), dtype=float32) 64 128 True None None
block Tensor("leaky_re_lu_7/sub:0", shape=(?, 32, 32, 256), dtype=float32) 32 256 True None None
block Tensor("leaky_re_lu_8/sub:0", shape=(?, 16, 16, 512), dtype=float32) 16 512 True None None
block Tensor("leaky_re_lu_9/sub:0", shape=(?, 8, 8, 512), dtype=float32) 8 512 True None None
block Tensor("leaky_re_lu_10/sub:0", shape=(?, 4, 4, 512), dtype=float32) 4 512 True None None
block Tensor("leaky_re_lu_11/sub:0", shape=(?, 2, 2, 512), dtype=float32) 2 512 True None None
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_3 (InputLayer) (None, 256, 256, 3) 0
__________________________________________________________________________________________________
conv_256 (Conv2D) (None, 128, 128, 64) 3136 input_3[0][0]
__________________________________________________________________________________________________
leaky_re_lu_5 (LeakyReLU) (None, 128, 128, 64) 0 conv_256[0][0]
__________________________________________________________________________________________________
conv_128 (Conv2D) (None, 64, 64, 128) 131072 leaky_re_lu_5[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 64, 64, 128) 512 conv_128[0][0]
__________________________________________________________________________________________________
leaky_re_lu_6 (LeakyReLU) (None, 64, 64, 128) 0 batch_normalization_4[0][0]
__________________________________________________________________________________________________
conv_64 (Conv2D) (None, 32, 32, 256) 524288 leaky_re_lu_6[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 32, 32, 256) 1024 conv_64[0][0]
__________________________________________________________________________________________________
leaky_re_lu_7 (LeakyReLU) (None, 32, 32, 256) 0 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv_32 (Conv2D) (None, 16, 16, 512) 2097152 leaky_re_lu_7[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 16, 16, 512) 2048 conv_32[0][0]
__________________________________________________________________________________________________
leaky_re_lu_8 (LeakyReLU) (None, 16, 16, 512) 0 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv_16 (Conv2D) (None, 8, 8, 512) 4194304 leaky_re_lu_8[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 8, 8, 512) 2048 conv_16[0][0]
__________________________________________________________________________________________________
leaky_re_lu_9 (LeakyReLU) (None, 8, 8, 512) 0 batch_normalization_7[0][0]
__________________________________________________________________________________________________
conv_8 (Conv2D) (None, 4, 4, 512) 4194304 leaky_re_lu_9[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 4, 4, 512) 2048 conv_8[0][0]
__________________________________________________________________________________________________
leaky_re_lu_10 (LeakyReLU) (None, 4, 4, 512) 0 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv_4 (Conv2D) (None, 2, 2, 512) 4194304 leaky_re_lu_10[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 2, 2, 512) 2048 conv_4[0][0]
__________________________________________________________________________________________________
leaky_re_lu_11 (LeakyReLU) (None, 2, 2, 512) 0 batch_normalization_9[0][0]
__________________________________________________________________________________________________
conv_2 (Conv2D) (None, 1, 1, 512) 4194816 leaky_re_lu_11[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 1, 1, 512) 0 conv_2[0][0]
__________________________________________________________________________________________________
convt.2 (Conv2DTranspose) (None, 4, 4, 512) 4194304 activation_1[0][0]
__________________________________________________________________________________________________
cropping2d_1 (Cropping2D) (None, 2, 2, 512) 0 convt.2[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 2, 2, 512) 2048 cropping2d_1[0][0]
__________________________________________________________________________________________________
dropout_1 (Dropout) (None, 2, 2, 512) 0 batch_normalization_10[0][0]
__________________________________________________________________________________________________
concatenate_2 (Concatenate) (None, 2, 2, 1024) 0 batch_normalization_9[0][0]
dropout_1[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, 2, 2, 1024) 0 concatenate_2[0][0]
__________________________________________________________________________________________________
convt.4 (Conv2DTranspose) (None, 6, 6, 512) 8388608 activation_2[0][0]
__________________________________________________________________________________________________
cropping2d_2 (Cropping2D) (None, 4, 4, 512) 0 convt.4[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 4, 4, 512) 2048 cropping2d_2[0][0]
__________________________________________________________________________________________________
dropout_2 (Dropout) (None, 4, 4, 512) 0 batch_normalization_11[0][0]
__________________________________________________________________________________________________
concatenate_3 (Concatenate) (None, 4, 4, 1024) 0 batch_normalization_8[0][0]
dropout_2[0][0]
__________________________________________________________________________________________________
activation_3 (Activation) (None, 4, 4, 1024) 0 concatenate_3[0][0]
__________________________________________________________________________________________________
convt.8 (Conv2DTranspose) (None, 10, 10, 512) 8388608 activation_3[0][0]
__________________________________________________________________________________________________
cropping2d_3 (Cropping2D) (None, 8, 8, 512) 0 convt.8[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 8, 8, 512) 2048 cropping2d_3[0][0]
__________________________________________________________________________________________________
dropout_3 (Dropout) (None, 8, 8, 512) 0 batch_normalization_12[0][0]
__________________________________________________________________________________________________
concatenate_4 (Concatenate) (None, 8, 8, 1024) 0 batch_normalization_7[0][0]
dropout_3[0][0]
__________________________________________________________________________________________________
activation_4 (Activation) (None, 8, 8, 1024) 0 concatenate_4[0][0]
__________________________________________________________________________________________________
convt.16 (Conv2DTranspose) (None, 18, 18, 512) 8388608 activation_4[0][0]
__________________________________________________________________________________________________
cropping2d_4 (Cropping2D) (None, 16, 16, 512) 0 convt.16[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 16, 16, 512) 2048 cropping2d_4[0][0]
__________________________________________________________________________________________________
concatenate_5 (Concatenate) (None, 16, 16, 1024) 0 batch_normalization_6[0][0]
batch_normalization_13[0][0]
__________________________________________________________________________________________________
activation_5 (Activation) (None, 16, 16, 1024) 0 concatenate_5[0][0]
__________________________________________________________________________________________________
convt.32 (Conv2DTranspose) (None, 34, 34, 256) 4194304 activation_5[0][0]
__________________________________________________________________________________________________
cropping2d_5 (Cropping2D) (None, 32, 32, 256) 0 convt.32[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 32, 32, 256) 1024 cropping2d_5[0][0]
__________________________________________________________________________________________________
concatenate_6 (Concatenate) (None, 32, 32, 512) 0 batch_normalization_5[0][0]
batch_normalization_14[0][0]
__________________________________________________________________________________________________
activation_6 (Activation) (None, 32, 32, 512) 0 concatenate_6[0][0]
__________________________________________________________________________________________________
convt.64 (Conv2DTranspose) (None, 66, 66, 128) 1048576 activation_6[0][0]
__________________________________________________________________________________________________
cropping2d_6 (Cropping2D) (None, 64, 64, 128) 0 convt.64[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 64, 64, 128) 512 cropping2d_6[0][0]
__________________________________________________________________________________________________
concatenate_7 (Concatenate) (None, 64, 64, 256) 0 batch_normalization_4[0][0]
batch_normalization_15[0][0]
__________________________________________________________________________________________________
activation_7 (Activation) (None, 64, 64, 256) 0 concatenate_7[0][0]
__________________________________________________________________________________________________
convt.128 (Conv2DTranspose) (None, 130, 130, 64) 262144 activation_7[0][0]
__________________________________________________________________________________________________
cropping2d_7 (Cropping2D) (None, 128, 128, 64) 0 convt.128[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 128, 128, 64) 256 cropping2d_7[0][0]
__________________________________________________________________________________________________
concatenate_8 (Concatenate) (None, 128, 128, 128 0 conv_256[0][0]
batch_normalization_16[0][0]
__________________________________________________________________________________________________
activation_8 (Activation) (None, 128, 128, 128 0 concatenate_8[0][0]
__________________________________________________________________________________________________
convt.256 (Conv2DTranspose) (None, 258, 258, 3) 6147 activation_8[0][0]
__________________________________________________________________________________________________
cropping2d_8 (Cropping2D) (None, 256, 256, 3) 0 convt.256[0][0]
__________________________________________________________________________________________________
activation_9 (Activation) (None, 256, 256, 3) 0 cropping2d_8[0][0]
==================================================================================================
Total params: 54,424,387
Trainable params: 54,414,531
Non-trainable params: 9,856
__________________________________________________________________________________________________